Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Exact solution of large-scale, asymmetric traveling salesman problems
ACM Transactions on Mathematical Software (TOMS)
Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators
Artificial Intelligence Review
Self-Organising Pattern Formation: Fruit Flies and Cell Phones
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Repair and Brood Selection in the Traveling Salesman Problem
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
| Hi-index | 0.00 |
This paper proposes an algorithm that incorporates parallel message passing with an evolutionary process that is applied to the traveling salesman problem (TSP). The algorithm is a parallel system that relies on each city sending messages to all the other cities. A dilating circle represents the messages transmitted from each city. The emerging route is dependent on the collision criteria of the dilating circles. Each city is prohibited from transmitting messages until its temporal delay has expired. The delays associated with each city may be different and are represented in a genetic algorithm (GA) which is used to optimise the search space. This technique is not restricted to the euclidean domian, unlike the analogy used to explain it. This representation of the TSP requires no repair algorithm. The algorithm is a heuristic method for finding a near optimal route and tests on several TSPLIB are reported.